ORIGINAL RESEARCH
Developing a Sediment Rating Curve Model Using the Curve Slope
Hamed Benisi Ghadim 1  
,  
Meysam Salarijazi 2  
,  
Iman Ahmadianfar 3  
,  
Mohammad Heydari 4  
,  
Ting Zhang 5  
 
 
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1
Department of Water Resources and Harbor Engineering, College of Civil Engineering, Fuzhou University, Fuzhou, China.
2
Department of Water Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
3
Department of Civil Engineering, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran
4
University of Malaya, Kuala Lumpur, Malaysia
5
Department of Water Resources and Harbor Engineering, College of Civil Engineering, Fuzhou University, Fuzhou, China
CORRESPONDING AUTHOR
Hamed Benisi Ghadim   

Fuzhou University
Online publication date: 2019-10-30
Publication date: 2020-01-16
Submission date: 2018-09-14
Acceptance date: 2019-01-30
 
Pol. J. Environ. Stud. 2020;29(2):1151–1159
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ABSTRACT
There are different ways to estimate suspended sediment load of a river. The conventional sediment rating curve model has been used widely due to its simplicity and required parameters. The most important limitation of the conventional SRC model is its relatively low precision and underestimation of the suspended sediment load in most studies. However, in this study, the concept of SRC model segmentation is introduced based on the curve slope under the title of developed SRC-S model. The most important feature is the simplicity of the presented application. To compare the conventional SRC and the developed SRC-S models, data from two hydrometry stations in northern Iran were selected. Graphical study of the models shows that the developed SRC-S model enjoys more fitting precision in comparison with the conventional SRC model, and also has improved underestimation error of suspended sediment load in higher rates of river flow discharge. Six numerical criteria for model accuracy (Nash-Sutcliffe, root-mean-square error, and mean absolute error, difference ratio, efficiency ratio improved and index of agreement) are used for quantitative comparison of the results of conventional and developed models. Accordingly, we found that the mentioned criteria have improved significantly compared to the conventional model.
eISSN:2083-5906
ISSN:1230-1485